Evaluation of the COSHH Essentials model with a mixture of organic chemicals at a medium-sized paint producer.

Lee EG, Slaven J, Bowen RB, Harper M - Ann Occup Hyg (2010)

Bottom Line:
This would not have been the same conclusion if some other chemical had been substituted (for example styrene, which has the same threshold limit value as toluene).However, it was difficult to override the reproductive hazard even though it was meant to be possible in principle.The experience of using the web-based COSHH Essentials model generated some suggestions to provide a more user-friendly tool to the model users who do not have expertise in occupational hygiene.

ABSTRACTThe Control of Substances Hazardous to Health (COSHH) Essentials model was evaluated using full-shift exposure measurements of five chemical components in a mixture [acetone, ethylbenzene, methyl ethyl ketone, toluene, and xylenes] at a medium-sized plant producing paint materials. Two tasks, batch-making and bucket-washing, were examined. Varying levels of control were already established in both tasks and the average exposures of individual chemicals were considerably lower than the regulatory and advisory 8-h standards. The average exposure fractions using the additive mixture formula were also less than unity (batch-making: 0.25, bucket-washing: 0.56) indicating the mixture of chemicals did not exceed the combined occupational exposure limit (OEL). The paper version of the COSHH Essentials model was used to calculate a predicted exposure range (PER) for each chemical according to different levels of control. The estimated PERs of the tested chemicals for both tasks did not show consistent agreement with exposure measurements when the comparison was made for each control method and this is believed to be because of the considerably different volatilities of the chemicals. Given the combination of health hazard and exposure potential components, the COSHH Essentials model recommended a control approach 'special advice' for both tasks, based on the potential reproductive hazard ascribed to toluene. This would not have been the same conclusion if some other chemical had been substituted (for example styrene, which has the same threshold limit value as toluene). Nevertheless, it was special advice, which had led to the combination of hygienic procedures in place at this plant. The probability of the combined exposure fractions exceeding unity was 0.0002 for the batch-making task indicating that the employees performing this task were most likely well protected below the OELs. Although the employees involved in the bucket-washing task had greater potential to exceed the threshold limit value of the mixture (P > 1 = 0.2375), the expected personal exposure after adjusting for the assigned protection factor for the respirators in use would be considerably lower (P > 1 = 0.0161). Thus, our findings suggested that the COSHH essentials model worked reasonably well for the volatile organic chemicals at the plant. However, it was difficult to override the reproductive hazard even though it was meant to be possible in principle. Further, it became apparent that an input of existing controls, which is not possible in the web-based model, may have allowed the model be more widely applicable. The experience of using the web-based COSHH Essentials model generated some suggestions to provide a more user-friendly tool to the model users who do not have expertise in occupational hygiene.

fig3: PER and full-shift measurements of acetone (upper row) and xylenes (lower row) for the bucket-washing task (note: the shaded areas represent the PER estimated from each control method).

Mentions:
For the bucket-washing task, the GM exposure for the acetone was 72.2 p.p.m., while exposures to the other chemicals in the mixture were <4 p.p.m. (Table 4). The comparison of exposure measurements with the PER estimated using CS 1 (50–500 p.p.m.) results in 12 measurements of the acetone exposures (66.7%) being within the range of the PER and ∼18% of the estimated distribution of likely acetone exposures would be above the COSHH Essentials predicted range (P > LU = 0.1810). For the other chemical components in the mixture, all measurements were below the lower limit of the PER estimated using CS 1 and the 95% probabilities of those chemicals being greater than the upper limit of the PER were <0.0004. When the exposure measurements were compared with the PER estimated using CS 2, the acetone and MEK showed moderate probability of observed exposures within the PER (LL < P < LU = 0.3266 for the acetone and 0.3571 for the MEK). More than half of the estimated distribution of the acetone exposures was above the COSHH Essentials predicted range (P > LU = 0.5733). Most exposure measurements for the other chemical components were below the lower level of the PER. When the exposure measurements were compared with the PER estimated using CS 3, all chemical components except for the acetone showed high or moderate probabilities of exposures being within the PER, while most acetone exposures were greater than the upper limit of the PER (P > LU = 0.8999). Fig. 3 shows examples of exposure measurements for the acetone and xylenes and PERs based on different control methods at the time of sample collection.

fig3: PER and full-shift measurements of acetone (upper row) and xylenes (lower row) for the bucket-washing task (note: the shaded areas represent the PER estimated from each control method).

Mentions:
For the bucket-washing task, the GM exposure for the acetone was 72.2 p.p.m., while exposures to the other chemicals in the mixture were <4 p.p.m. (Table 4). The comparison of exposure measurements with the PER estimated using CS 1 (50–500 p.p.m.) results in 12 measurements of the acetone exposures (66.7%) being within the range of the PER and ∼18% of the estimated distribution of likely acetone exposures would be above the COSHH Essentials predicted range (P > LU = 0.1810). For the other chemical components in the mixture, all measurements were below the lower limit of the PER estimated using CS 1 and the 95% probabilities of those chemicals being greater than the upper limit of the PER were <0.0004. When the exposure measurements were compared with the PER estimated using CS 2, the acetone and MEK showed moderate probability of observed exposures within the PER (LL < P < LU = 0.3266 for the acetone and 0.3571 for the MEK). More than half of the estimated distribution of the acetone exposures was above the COSHH Essentials predicted range (P > LU = 0.5733). Most exposure measurements for the other chemical components were below the lower level of the PER. When the exposure measurements were compared with the PER estimated using CS 3, all chemical components except for the acetone showed high or moderate probabilities of exposures being within the PER, while most acetone exposures were greater than the upper limit of the PER (P > LU = 0.8999). Fig. 3 shows examples of exposure measurements for the acetone and xylenes and PERs based on different control methods at the time of sample collection.

Bottom Line:
This would not have been the same conclusion if some other chemical had been substituted (for example styrene, which has the same threshold limit value as toluene).However, it was difficult to override the reproductive hazard even though it was meant to be possible in principle.The experience of using the web-based COSHH Essentials model generated some suggestions to provide a more user-friendly tool to the model users who do not have expertise in occupational hygiene.

ABSTRACTThe Control of Substances Hazardous to Health (COSHH) Essentials model was evaluated using full-shift exposure measurements of five chemical components in a mixture [acetone, ethylbenzene, methyl ethyl ketone, toluene, and xylenes] at a medium-sized plant producing paint materials. Two tasks, batch-making and bucket-washing, were examined. Varying levels of control were already established in both tasks and the average exposures of individual chemicals were considerably lower than the regulatory and advisory 8-h standards. The average exposure fractions using the additive mixture formula were also less than unity (batch-making: 0.25, bucket-washing: 0.56) indicating the mixture of chemicals did not exceed the combined occupational exposure limit (OEL). The paper version of the COSHH Essentials model was used to calculate a predicted exposure range (PER) for each chemical according to different levels of control. The estimated PERs of the tested chemicals for both tasks did not show consistent agreement with exposure measurements when the comparison was made for each control method and this is believed to be because of the considerably different volatilities of the chemicals. Given the combination of health hazard and exposure potential components, the COSHH Essentials model recommended a control approach 'special advice' for both tasks, based on the potential reproductive hazard ascribed to toluene. This would not have been the same conclusion if some other chemical had been substituted (for example styrene, which has the same threshold limit value as toluene). Nevertheless, it was special advice, which had led to the combination of hygienic procedures in place at this plant. The probability of the combined exposure fractions exceeding unity was 0.0002 for the batch-making task indicating that the employees performing this task were most likely well protected below the OELs. Although the employees involved in the bucket-washing task had greater potential to exceed the threshold limit value of the mixture (P > 1 = 0.2375), the expected personal exposure after adjusting for the assigned protection factor for the respirators in use would be considerably lower (P > 1 = 0.0161). Thus, our findings suggested that the COSHH essentials model worked reasonably well for the volatile organic chemicals at the plant. However, it was difficult to override the reproductive hazard even though it was meant to be possible in principle. Further, it became apparent that an input of existing controls, which is not possible in the web-based model, may have allowed the model be more widely applicable. The experience of using the web-based COSHH Essentials model generated some suggestions to provide a more user-friendly tool to the model users who do not have expertise in occupational hygiene.